IFDlong: a model-based isoform and fusion detector for accurate annotation and quantification of long-read RNA-seq data.

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Authors: Wenjia Wang, Jia-Jun Liu, Yuzhen Li, Sungjin Ko, Ning Feng, Manling Zhang, Qingqi Lin, Mengying Xia, Yan Ping Yu, Jian-Hua Luo, Pedro Baldoni, George Tseng
+1 more Silvia Liu
Cited by: 1

Abstract

Long-read transcriptome sequencing (long-RNA-seq) revolutionizes transcriptome research by enabling full-length transcript analysis for comprehensive exploration of isoform diversity. We developed IFDlong, a probabilistic framework and software suite for detecting isoform and fusion transcripts from bulk or single-cell long-RNA-seq data. IFDlong annotates each long read, identifies novel isoforms, quantifies expression via an expectation-maximization algorithm, and profiles fusion transcripts. In large-scale simulation and real data analyses, IFDlong outperforms existing tools and demonstrated high accuracy and robustness across multiple in-house and public datasets, including healthy tissues, cell lines, and different diseases.

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
25 February 2026
Language
EN